Update index.html

index.html

@@ -340,9 +340,15 @@
 </div>
 
 <script>
-    const models = ["best_model.onnx", "model_epoch_1_acc_0.9849.onnx", "model_epoch_2_acc_0.9885.onnx", "model_epoch_3_acc_0.9865.onnx", "model_epoch_4_acc_0.9874.onnx", "model_epoch_5_acc_0.9877.onnx", "model_epoch_6_acc_0.9901.onnx", "model_epoch_7_acc_0.9908.onnx", "model_epoch_8_acc_0.9912.onnx", "model_epoch_9_acc_0.9909.onnx", "model_epoch_10_acc_0.9411.onnx", "model_epoch_11_acc_0.9929.onnx", "model_epoch_12_acc_0.9922.onnx", "model_epoch_13_acc_0.9918.onnx", "model_epoch_14_acc_0.9922.onnx", "model_epoch_15_acc_0.9925.onnx", "model_epoch_16_acc_0.9906.onnx", "model_epoch_17_acc_0.9908.onnx", "model_epoch_18_acc_0.9926.onnx", "model_epoch_19_acc_0.9916.onnx", "model_epoch_20_acc_0.9915.onnx"];
+    // --- 変更部分: モデルリストに仕様(type)を明記して定義 ---
+    const models = [
+        { file: "tinymodelV3.onnx", type: "hsc" },     // 異常検知スコア (1出力)
+        { file: "tinymodelV2.onnx", type: "softmax" } // 通常の分類 (2出力)
+    ];
+
     let session = null;
     let isReady = false;
+    let currentModelConfig = null; // 現在選択されているモデルの設定を保持
 
     const modelSelect = document.getElementById('modelSelect');
     const fileInput = document.getElementById('fileInput');
@@ -354,28 +360,30 @@
     const resultOutput = document.getElementById('resultOutput');
 
     function initSelect() {
-        models.forEach(m => {
+        models.forEach((m, index) => {
             const opt = document.createElement('option');
-            opt.value = m;
-            opt.textContent = m;
+            opt.value = index; // インデックスをvalueに設定
+            opt.textContent = m.file;
             modelSelect.appendChild(opt);
         });
-        modelSelect.addEventListener('change', (e) => loadModel(e.target.value));
+        // 選択時に該当するオブジェクトを渡す
+        modelSelect.addEventListener('change', (e) => loadModel(models[e.target.value]));
     }
 
-    async function loadModel(modelName) {
+    async function loadModel(modelConfig) {
         isReady = false;
         submitBtn.disabled = true;
-        statusText.innerText = "⏳ " + modelName + " をロード中...";
+        currentModelConfig = modelConfig;
+        statusText.innerText = "⏳ " + modelConfig.file + " をロード中...";
         
         try {
             if (session) {
                 await session.release();
                 session = null;
             }
-            session = await ort.InferenceSession.create('./' + modelName);
+            session = await ort.InferenceSession.create('./' + modelConfig.file);
             isReady = true;
-            statusText.innerText = "✅ " + modelName + " の準備完了";
+            statusText.innerText = "✅ " + modelConfig.file + " の準備完了";
             
             if (previewImg.src && previewImg.style.display !== 'none') {
                 submitBtn.disabled = false;
@@ -408,62 +416,64 @@
         const ctx = canvas.getContext('2d');
         ctx.drawImage(imgElement, 0, 0, 224, 224);
         const data = ctx.getImageData(0, 0, 224, 224).data;
-
         const mean = [0.485, 0.456, 0.406];
         const std = [0.229, 0.224, 0.225];
         const floatData = new Float32Array(3 * 224 * 224);
-
         for (let i = 0; i < 224 * 224; i++) {
             const r = data[i * 4] / 255.0;
             const g = data[i * 4 + 1] / 255.0;
             const b = data[i * 4 + 2] / 255.0;
-
             floatData[i] = (r - mean[0]) / std[0];
             floatData[224 * 224 + i] = (g - mean[1]) / std[1];
             floatData[2 * 224 * 224 + i] = (b - mean[2]) / std[2];
         }
-
         return new ort.Tensor('float32', floatData, [1, 3, 224, 224]);
     }
 
     submitBtn.addEventListener('click', async () => {
-        if (!isReady || !session || !previewImg.src) return;
+        if (!isReady || !session || !previewImg.src || !currentModelConfig) return;
         
         submitBtn.disabled = true;
         statusText.innerText = "⚡ 推論中...";
-
         try {
             const inputTensor = await preprocess(previewImg);
             const feeds = {};
             feeds[session.inputNames[0]] = inputTensor;
-
+            
             const start = performance.now();
             const results = await session.run(feeds);
             const duration = (performance.now() - start).toFixed(1);
-
+            
             const output = results[session.outputNames[0]].data;
-            const exp0 = Math.exp(output[0]);
-            const exp1 = Math.exp(output[1]);
-            const sum = exp0 + exp1;
-            const probNeed = (exp0 / sum) * 100;
-            const probTrash = (exp1 / sum) * 100;
+            let probNeed, probTrash;
+
+            // --- 事前定義されたモデルの仕様(type)に基づいて計算を分岐 ---
+            if (currentModelConfig.type === "hsc") {
+                const trashScore = output[0];
+                probTrash = trashScore * 100;
+                probNeed = (1.0 - trashScore) * 100;
+            } else if (currentModelConfig.type === "softmax") {
+                const exp0 = Math.exp(output[0]);
+                const exp1 = Math.exp(output[1]);
+                const sum = exp0 + exp1;
+                probNeed = (exp0 / sum) * 100;
+                probTrash = (exp1 / sum) * 100;
+            }
 
             // UI Render
             emptyOutput.style.display = 'none';
             resultOutput.style.display = 'flex';
-
             const topClass = probNeed >= probTrash ? "need" : "trash";
             const topConf = Math.max(probNeed, probTrash).toFixed(1);
-
+            
             document.getElementById('topClassName').innerText = topClass;
             document.getElementById('topClassConf').innerText = "信頼度: " + topConf + "%";
-
+            
             document.getElementById('probNeedText').innerText = probNeed.toFixed(1) + "%";
             document.getElementById('probNeedBar').style.width = probNeed + "%";
-
             document.getElementById('probTrashText').innerText = probTrash.toFixed(1) + "%";
             document.getElementById('probTrashBar').style.width = probTrash + "%";
-
+            
             statusText.innerText = "✅ 完了 (" + duration + "ms)";
         } catch (e) {
             statusText.innerText = "❌ エラー: " + e.message;